[{"data":1,"prerenderedAt":4},["ShallowReactive",2],{"article-doc:docs\u002Fconcepts\u002Fcontext-aware-processing":3},"---\ntitle: Context-Aware Processing\ndescription: Speech is ambiguous when interpreted in isolation. Context is part of recognition, not a post-processing step.\n---\nSpeech is ambiguous when interpreted in isolation.\n\nA short audio fragment may contain multiple plausible interpretations. Additional speech often makes the intended meaning clearer.\n\nConsider:\n\n```text\nLet's send it to Alex...\nLet's send it to Alex Chen...\nLet's send it to Alex Chen after the review.\n```\n\nThe later context changes how earlier information should be interpreted and structured.\n\n## Context is part of recognition\n\nLansonAI treats live speech as an evolving context rather than a sequence of independent audio fragments.\n\nThis allows the system to use surrounding information when resolving ambiguity.\n\nContext can help with:\n\n- ambiguous words\n- names and terminology\n- sentence boundaries\n- corrections\n- semantic continuity\n- translation\n\n## Context does not mean waiting for completion\n\nA system could obtain maximum context simply by waiting until the speaker finishes.\n\nThat would defeat the purpose of real-time processing.\n\nThe challenge is therefore:\n\n> Use enough context to improve interpretation without turning live speech into offline transcription.\n\nThis tradeoff is central to LansonAI's real-time architecture.\n\n## Context accumulates over time\n\nConceptually:\n\n```text\naudio₁ → interpretation₁\n\naudio₂\n  + previous context\n  → interpretation₂\n\naudio₃\n  + accumulated context\n  → interpretation₃\n```\n\nThe system continuously updates its understanding as new evidence arrives.\n\nApplications therefore receive speech as an evolving stream of context rather than a collection of isolated recognition requests.\n",1790059118949]